Fungal infection of agricultural crops including cereals and grains, leaf crops and horticultural crops causes serious losses of value and nutrition around the world. Anti-fungal agents can be costly to purchase and use, and can be toxic or otherwise detrimental to some off-target animals and vegetation near to the site of application and in runoff affecting the watershed. It is therefore beneficial to farmers, consumers and their surrounding communities to use as little anti-fungal agent as possible, while continuing to control fungal growth to maximize crop yield. One way to to minimize the use of anti-fungal agents is to utilize anti-fungal compositions whose anti-fungal agents synergize with each other to provide an equal or better fungal control while using lessened amounts of anti-fungal agents used to accomplish that goal.
However, large-scale experimental drug combination studies have found that synergistic drug pairs are extremely complex and rare, with only a 4-10% probability of finding synergistic drug pairs [Yin et al., PLOS 9:e93960 (2014); Cokol et al., Mol. Systems Biol. 7:544 (2011)]. In fact, a systematic screening of about 120,000 two-component drug combinations based on reference-listed drugs found fewer than 10% synergistic pairs, as well as only 5% synergistic two-component pairs for fluconazole, a triazole anti-fungal compound similar to compounds in the FRAC Code G1, discussed below, that has the same mode of action [Borisy et al., Proc. Natl Acad. Sci. 100:7977-7982 (2003)].
Due to the complex nature of drug-drug interaction, synergy needs to be determined, not predicted. Determination of synergy can be efficiently performed through high throughput screening, but prediction of synergy is difficult. According to Dr. Chou, “If synergy is predictable, then there would be no need to conduct drug combination studies. Sometimes, the prediction might be correct by luck but it will not be quantitative. Frequently, predictions were done after the observed facts retrospectively, as can be seen in the biomedical literature” [Chou, Cancer Res. 70:440-446 (2010)].
A median-effect equation for a single drug effect has been extended to a multiple drug effect equation for n drugs. The equation provides the theoretical basis for the fractional inhibitory concentration index (FICI) isobologram equation that permits quantitative determination of drug interactions, where FICI <1, =1, and >1 indicate synergism, additive effect, and antagonism, respectively. Based on these algorithms, computer software has been developed to permit automated determination of synergism and antagonism at all dose or effect levels.
Such data analyses have facilitated dose-effect analysis for single drug evaluation or carcinogen and radiation risk assessment, as well as for drug or other entity combinations in a vast field of disciplines of biomedical and agricultural sciences. The merging of the mass-action law principle with mathematical induction-deduction has been shown to be a unique and effective scientific method for general theory development. Chou, Pharmacol Rev 58:621-681 (2006).
One of the major objectives of having a synergistic drug combination is to reduce the dose of the drug used, thereby reducing the toxicity while maintaining efficacy. The concept of the dose-reduction index [DRI] was formally introduced by Chou and co-workers in 1988 [Chou et al., Pharmacologist 30:A231 (1988)] and has since been used in many publications. The DRI is a measure of how many-fold the dose of each drug in a synergistic combination can be reduced at a given effect level compared with the doses of each drug alone.
Chou and Talalay in 1983 [Chou et al., Trends Pharmacol 4:450-454 (1983)] used the term combination index (CI, now often referred to as FICI or fractional inhibitory concentration index) for quantification of synergism or antagonism for two drugs where FICI <1, =1, and >1, indicate synergism, additive effect, and antagonism, respectively. The equation for determining FICI is shown below, where D1 and D2 are the two doses of active agents. In the denominator, (Dx)1 is for D1
  FICI  =                              (          D          )                1                              (                      D            x                    )                1              +                            (          D          )                2                              (                      D            x                    )                2            “alone” that inhibits a system x %, and (Dx)2 is for D2 “alone” that inhibits a system x %. The (Dx)1 and (Dx)2 values can be calculated as discussed in Chou, Pharmacol Rev 58:621-681 (2006). In the numerators, (D)1+(D)2 “in combination” also inhibit x %. If the sum of these two fractional terms is equal to 1, additive action is indicated. If the FICI value is smaller than 1, synergism is indicated, and if the FICI value is greater than 1, antagonism is indicated.
The dose reduction index (DRI) is obtained by inverting each term of the above equation. Thus, for a two drug combination:
  FICI  =                                          (            D            )                    1                                      (                          D              x                        )                    1                    +                                    (            D            )                    2                                      (                          D              x                        )                    2                      =                  1                              (            DRI            )                    1                    +              1                              (            DRI            )                    2                    Although DRI >1 is beneficial, it does not necessarily indicate synergism because, from the above equation, an additive effect or even slight antagonism can also lead to DRI >1. As noted in Chou, Pharmacol Rev 58:621-681 (2006), Table 4 on page 637, numerical values for FICI have been developed that are indicative of synergy, additivity or antagonism. The values shown in that table are set out below. Computer software developed
Range of FICIDescription  <0.1Very strong synergism0.1-0.3Strong synergism0.3-0.7Synergism 0.7-0.85Moderate synergism0.85-0.90Slight synergism0.90-1.10Nearly additive1.10-1.20Slight Antagonism1.20-1.45Moderate Antagonism1.45-3.3 Antagonism3.3-10 Strong antagonism>10Very strong antagonismby Chou and co-workers is also available commercially from ComboSyn, Inc. of Paramus, N.J., for use in calculating the CI and DRI values.
The designations based on FICI values of Chou's Table 4, above, notwithstanding, others have taken a more conservative approach to use of such values to assert the presence of synergy. Thus, the article of Odds [J. Antimicrob. Chemother. 52:1 (2003)] notes that for several reasons, that journal will require authors submitting papers containing FICI data to use the interpretations of ‘synergy’ (FICI ≦0.5), ‘antagonism’ (FICI >4.0) and ‘no interaction’ (FICI >0.5-4.0). That usage was said to also foster conservative interpretations of the data, in that some combinations of agents can exert inhibitory effects that are more than the sum of their effects alone (FICI <1.0) or less than their effects alone (FICI >1.0). Comparatively, the more conservative approach excludes the “Moderate synergism” and “Slight synergism” taught in Chou, Pharmacol Rev 58:621-681 (2006). The publication by Barbee et al. [Antimicrob. Agents Chemother., 69:1572-1578 (2014)] utilizes that measure.
Fungal infections of substrates such as plants, animals, food stuffs and drinks such as wine and beer can have both positive and negative financial, health and other effects upon society, depending on what it is that is infected. Several anti-fungal compounds have been developed and approved for use on those infected substrates where such an infection can have a detrimental effect.
Anti-fungal agents have been found to act by one or more mechanisms and are frequently grouped or classed by the mechanism of action by which the agent kills fungi or inhibits fungal growth. One classification system used widely in the industry is that of FRAC, the Fungicide Resistance Action Committee, which is a specialist technical group of Crop Life International (CLI). CLI is itself a global network of companies and associations that deal in plant biotechnology and crop protection.
The Fungicide Resistance Action Committee (FRAC) is an international organization made up of representatives of the agrochemical industry whose mission is to provide fungicide resistance management guidelines to prolong the effectiveness of fungicides and to limit crop losses should resistance occur. FRAC publishes a Code List (version updated on February 2015) of different letters (A to I, with added numbers) that are used to distinguish fungicide compositions according to their biochemical mode of action (MOA) in fungal plant pathogens. The grouping was made according to processes in metabolism ranging from nucleic acid synthesis (A) to secondary metabolism, e.g. melanin synthesis (I) at the end of the list, followed by host plant defense inducers (P), recent molecules with an unknown mode of action and unknown resistance risk (U, transient status, mostly not longer than 8 years, until information about mode of action and mechanism of resistance becomes available), and multi-site inhibitors (M).
Within a given mode of action such as “nucleic acid synthesis” inhibitors, the FRAC code also lists a target site and code such as “A1: RNA polymerase I”, “A2: adenosine deaminase”, “A3: DNA/RNA synthesis”, etc. A group name is also provided for each code number such as “fungicides” for A1, and the groups can be sub-divided by “chemical group”, which for A1 are three: “acylalanines”, “oxazolidinones” and “butyrolactones”. The common names of various commercially available antifungal compounds in each chemical group are also provided. A FRAC Code number is also provided for each target site and letter-number code, although the FRAC code “number” and the letter-number code for the P group and the M group are each the same letter-number codes.
According to FRAC recommendations for fungicide mixtures designed to delay resistance evolution, FRAC, page 2, January 2010, fungicides are often combined as co-formulations or tank mixes for several reasons that can be conveniently divided into three categories:
1. Improved disease control. Mixtures can be used to broaden the spectrum of disease control of a product.
2. Disease control security when resistance is present.
3. Resistance management. When used for resistance management it is necessary for at least two components of the mixture to have activity against the field populations of the target pathogen when used alone. Note that none of these address synergism, which is not understood to be a commonly applied criterion in the use of anti-fungals to control plant pathogens.
Although the FRAC code identifiers were originally intended for use in minimizing crop resistance to fungicides by their mode of action (MOA), the FRAC codes and the fungicides associated with those codes have other uses as are discussed hereinafter. The fungal species and/or strain that can be controlled (whose growth can be inhibited or stopped) by a particular fungicide is known in the art from the product label, licensing by governmental agencies such as the Environmental Protection Agency (EPA) in the United States, and the Pest Management Regulatory Agency (PMRA) in Canada, as well as by literature reports, and can be correlated back to the MOA of that fungicide and thereby to a FRAC code.
Anti-fungal agents are or can be looked upon as pharmaceutical products. Such agents can cause harmful side effects if used on one substrate and then ingested or contacted with the skin or eyes of an animal such as a human.
Captan, a phthalimide with a FRAC code of M4, is among the largest selling fungicides, and is reported to be relatively non-toxic to humans and birds, but is toxic to fish. Captan has been found to cause cancer in male and female mice at high doses and is chemically similar to pesticides that have been shown to cause cancer.
Triazoles, with a FRAC Code of G1, and strobilurins, with a FRAC Code of C3, inhibit C14-demethylase in sterol biosynthesis and cytochrome bc1, respectively, account for about 35 percent of the 8.9 billion dollar fungicide market as of 2005. These compounds are typically sprayed on to crops. Each of those chemical groups encompasses several different fungicides. Fishel, [Document PI-68, Agronomy Department, UF/IFAS Extension, original publication September 2005, revised March 2014] reported that the triazoles are relatively non-toxic orally to mammals, but some are listed as possible human carcinogens. Like captan, the triazoles as a group are generally not toxic to birds nor to bees, but are moderately to highly toxic to fish. A study of three widely-used strobilurins indicated potential toxic effects on the early development of grass carp. [Liu et al., Ecotoxica Environ Saf 98:297-302 (December 2013).]
Benzoxyborole preparations and uses are the subject of several US patents, including U.S. Pat. No. 7,582,621; U.S. Pat. No. 7,767,657; U.S. Pat. No. 7,816,344; and U.S. Pat. No. 8,168,614. Many of the uses of those compounds are as antibiotics, with U.S. Pat. No. 7,816,344 teaching at column 1, lines 37-41, certain classes of oxaboroles of Formula A that are monosubstituted at the -3, 6- or
-7 position or disubstituted at the 3-/6-, or -3/-7 positions are surprisingly effective antibacterials.
U.S. Pat. No. 7,767,657 teaches and claims that a 5-fluorobenzoxyborole of Formula B and its salts
are useful in a composition for topical or foliar administration to an animal suffering from an infection from a microorganism, and particularly exemplifies yeasts and molds as the microorganism treated.
US Patent Publication No. 20140259230 published Sep. 11, 2014 teaches the use of several oxaborole compounds for protecting plants and plant propagation materials from phytopathogens. One group of oxaboroles were disclosed to be those of Formula B-1
in which the possible combinations of R, R7 and X amount to more than 100 million compounds. Those substituents in a further preferred embodiment were F for R7, CH2 for X and R was H, C1-C4alkyl optionally substituted by —NR3R4 wherein R3 and R4 are each independently hydrogen, optionally substituted C1-C4alkyl. A composition containing a compound of Formula B-1 was said to be useful in a method of protecting plants or plant propagation materials against phytopathogenic fungi belonging to several classes. The above published application teaches the use of several oxaboroles at concentrations ranging from 200 to 20 parts per million (ppm) to obtain between 80 and 20 percent control of fungal growth on infected plants, seeds and plant propagation materials.
Benzoxaboroles of Formula B-1 are known to inhibit aminoacyl tRNA synthetases, which are a family of enzymes responsible for attaching specific amino acids to the appropriate tRNAs. The ribosome then transfers the amino acids from the tRNAs onto the protein being synthesized. Benzoxaboroles selectively target the editing domain of the enzyme, leading to mis-incorporation of amino acids into proteins and subsequent failure of normal protein production needed for cell survival [Liu, et al. (2014) Bioorg. Med. Chem. 22:4462-4473].
Although benzoxaboroles have been known to be general anti-microbial agents by disrupting the target organism's DNA translation processes, not much is known regarding how disruption of DNA translation might affect other biological systems within the same organism. More specifically, it is not known how the disruption of DNA translation by benzoxaboroles might affect the target organism's sensitivity to other anti-microbial chemicals that disrupt biological processes other than those mediated by Leucyl-tRNA synthetase. If benzoxaborole and another non-benzoxaborole compound can separately disrupt two or more distinct biological processes, they can have an effect greater than the sum of that induced in separate treatments of the target organism. Thus, identifying synergistic combinations is an important strategy for obtaining effective biological controls.
Synergism can potentially also work by cooperativity if two anti-microbial compounds affect each other's binding at different sites on the same molecule. Such cooperativity occurs naturally in biological systems and has powerful effects on e.g. ligand-gated ion channels and the function of hemoglobin in gas exchange, yet the complexity of protein structure makes cooperative and allosteric effects extremely difficult to predict. Cooperative interactions of multiple distinct drugs binding to different sites on the same target molecule are known [Hartman et al., Biochem Pharmacol. 97(3):341-349 (Oct. 1, 2015)] but are apparently not common or expected.
In view of the ancillary toxicity and potential carcinogenicity exhibited by fungicides along with the beneficial crop-saving and disease fighting attributes of the same materials, it would be advantageous if the potential for the detrimental side effects of fungicidal use could be minimized, while maintaining high anti-fungal activity and use of less of those compounds. The present invention that is described hereinafter provides one means for maintaining or enhancing benefits and minimizing detriments of the use of particular fungicidal groups with specific fungi.